Method and apparatus for remote medical monitoring incorporating video processing and system of motor tasks

ABSTRACT

Video image data is received in the form of a sequence of images representative of a subject performing one or more predetermined tasks within a new environment (FIG.  3  element  31 ). A plurality of silhouettes is generated from the video image data and combined to provide a motion portrait (FIG.  6 ). Motion characteristics are then calculated based on the motion portrait and may be compared with normal or previous motion characteristics as part of diagnostic analysis ( 38 ).

CROSS REFERENCE TO RELATED APPLICATIONS

Related subject matter is found in U.S. Pat. No. 5,441,047, and U.S.Pat. No. 5,544,649, the teachings of which patents are herebyincorporated by this reference. Additional related subject matter isfound in U.S. Provisional Patent Application Serial No. 60/205,186 filedMay 18, 2000 entitled “Method And Apparatus For Facilitating MedicalPre-Screening” assigned to the same assignee of the present inventionand U.S. Provisional Patent Application Serial No. 60/205,279 entitledMethod and Apparatus for Remote Medical Monitoring Incorporating VideoProcessing and System of Motor Tasks filed May 18, 2000, assigned to thesame assignee, incorporated herewith by reference and for which priorityis claimed.

TECHNICAL FIELD

The present invention relates to techniques for monitoring the medicalcondition of a subject or subject/patient most especially neuromuscularmotor activity, and, to a method and apparatus for monitoring a subjector subject/patient at a remote site from a central station by means ofinteractive visual, audio and data transmission communications. Whilethe invention is also suitable for use in any situation where anysubject or subject/patient is to be monitored at a site remote from acentral station, an important application is the monitoring and caringfor the elderly (both well and ill persons) in the home environment.Thus, the present invention can also be said to relate to the field ofgeriatric care. Further, the techniques disclosed may also be utilizedin a hospital or clinic setting inasmuch as they constitute diagnostictechniques useful for any person and at any local or remote location.Additionally the techniques and methods have application to otherdisciplines including, but not limited to, psychological diagnosis andmonitoring, and interrogation monitoring and analysis. Finally, theinvention enables conduct of physiological analysis utilizing a singlevideo camera and without markers.

BACKGROUND OF THE INVENTION

Ambulatory Care in General

Most of the resources for modern medicine have been invested in thedevelopment of highly sophisticated hospital facilities. Therefore,institutional patient care has become prohibitively expensive, in manycases overused and for a substantial number of patients potentiallyharmful. The tendency to substitute costly institutional patient carewith effective and cost containing extra-institutional, ambulatorymedical facilities is gaining rapid momentum. These attempts however arestill confined to the delivery of care in outpatient clinics to whichthe patient has to come to obtain medical care, or home nurse visitswhich are short, scarce, and insufficient. The combination of growingsophistication in ambulatory monitoring technology together with theexplosive development of telecommunication provides the ideal substrateto enable the development of highly sophisticated, reliable andaffordable, remotely controlled, remote monitoring capabilities whichcan monitor, analyze and assess many physiological parameters in anypotential subject and in any possible location. Such a system isspecially suited to provide a sophisticated platform or home carefacilities for a wide spectrum of subject/patient.

The described invention is a neuromuscular and motor activity remotemonitoring system for any person in need of remote assessment ofphysiological, psychological, and other parameters. From thesubject/patient care aspect one of the important applications of thissystem is monitoring and care of the elderly geriatric population. Thisis due to the complexity of the holistic approach to geriatric care,which will be elaborated below.

Geriatric Ambulatory Home Monitoring

Modern society with its improvement in living conditions and advancedhealth care has brought about a marked prolongation of life expectancy.This change has resulted in a dramatic and progressive increase in thegeriatric population. A large percentage of the geriatric populationneeds continuous general, as well as medical, supervision and care. Forexample, supervision of daily activities such as dressing, personalhygiene, eating and safety as well as supervision of their health statusis necessary. Furthermore, the relief of loneliness and anxiety is amajor, yet unsolved, problem to be addressed. These and other facets ofthe management of the ever increasing geriatric population have yet tobe successfully addressed and solved.

The creation of retirement facilities and old age homes, as well asother geriatric facilities, provide only a partial solution to theproblems facing the geriatric population. The geriatric population, aconstantly increasing fraction of society, has become increasinglydependent upon the delivery of home health and general care, which hasits own set of challenges and drawbacks.

The notion of ambulatory (home environment) subject/patient care isgaining increased popularity and importance. This shift insubject/patient care from the “sheltered” institutional milieu to thesubject/patient's home, work place, or recreational environment is dueprimarily to a radical change in concepts. That is, specialists ingeriatric care now tend to keep the aged in their own naturalenvironment for as long as possible.

Except for scarce model organizations, home care is still carried outeither by the subject/patient's family or by nonprofessional help, or,in the usual circumstance, by professional, highly trained personnel atvery significant expense. The monitoring equipment at home carefacilities is usually minimal or nonexistent, and the subject/patienthas to be transported to the doctor's office or other diagnosticfacility to allow proper evaluation and treatment.

Subject/patient follow-up is presently done by means of home visits ofnurses which are of sporadic nature, time consuming and generally veryexpensive. A visiting nurse can perform about 5-6 home visits per day.The visits have to be short and can usually not be carried out on adaily basis. Moreover, a visiting nurse program provides no facilitiesfor continuous monitoring of the subject/patient and thus nosophisticated care, except in fortuitous circumstances, in times ofemergency. The remainder of day after the visiting nurse has left isoften a period of isolation and loneliness for the subject/patient. Theexisting home care nursing facilities divert skilled nurses, a scarcecommodity, from the hospital environment and uses them in a highlyinefficient manner due to the wide dispersion of the subject/patientsand the lack of sophisticated diagnostic facilities in thesubject/patient's home. Clearly, the practice of visiting nurses leavesmuch to be desired.

These considerations apply to the general population as well, as thespiraling cost of hospital care has lead to a dramatic increase in theuse of outpatient care as a treatment modality.

Falls and Injuries in the Aged

Additional facts support development of an improved home health caresystem especially for a geriatric population. In particular, falls are amajor health problem among the elderly, causing injury, disability anddeath. One third (some studies suggest half) of those over the age of 65suffer at least one fall each year. The rate of falling increases to 40%among those who exceed the age of 80. According to the National SafetyCouncil, falls accounted for one-third of the death total for theelderly. Those who survive falls may have restricted activity,soft-tissue injuries, or fractures. It is estimated that up to 5% offalls by elderly persons result in fractures. A similar percent resultin soft-tissue injury requiring hospitalization or immobilization for anextended period. It is estimated that hip fractures resulting from fallscost approximately $2 billion in the United States during 1980. Fallsare mentioned as a contributing factor to admissions to nursing homes.

The factors leading to falls can be divided into two main groups:environmental factors and medical factors. In spite of the difficulty inthe surveillance of subject/patient condition before a fall, almost allresearchers share the conclusion that environmental hazards aredecreasingly important in causing falls as age increases. A clearcorrelation between clinical or medical problems and the incident offalls by the elderly has been established. Many of these medicalproblems of the elderly or infirm can be detected by simple clinicalobservation. For example gait and balance abnormality may indicatedifficulty with neurologic and musculoskeletal functions that maycontribute to physical instability. Changes in gait can be identified bythe following: slow speed, short step length, narrow stride width, widerange of stepping frequency, a large variability of step length, andincreasing variability with increasing frequency.

Thus, there are relatively straightforward techniques that enablediagnosis of a predisposition or likelihood of falls among the elderly.U.S. Pat. Nos. 5,441,047 and 5,544,649 (“the '047 and '649 patents”)disclose inexpensive procedures for undertaking such diagnoses orinvestigating such predispositions in a large subject/patient populationwherein the kinematic condition of the subject/patient can beinvestigated or where the appearance, and reflex activity of thesubject/patient can be investigated with ease. In particular, the '047and '649 patents describe an ambulatory (in the home) subject/patienthealth monitoring system wherein a health care worker at a centralstation monitors the subject/patient, while the subject/patient is at aremote location. The subject/patient may be a person having a specificmedical condition being monitored or may be an elderly person desiringgeneral medical surveillance in the home environment. Video transmissioncameras are provided at the subject/patient's remote location and at thecentral station such that the subject/patient and the health care workerare in interactive visual and audio communication. A communicationsnetwork such as an interactive cable television is used for thispurpose. Various medical condition sensing and monitoring equipment areplaced in the subject/patient's home, depending on the particularmedical needs of the subject/patient. The subject/patient's medicalcondition is measured or sensed in the home and the resulting data istransmitted to the central station for analysis and display. The healthcare worker then is placed into interactive visual communication withthe subject/patient concerning the subject/patient's general well being,as well as the subject/patient's medical condition. Thus, the healthcare worker can make “home visits” electronically, twenty-four hours aday, seven days a week in a non-intrusive, cost effective, privacyprotecting manner.

Prior Art Testing Techniques

While the '047 and '649 patents (incorporated herewith by reference)represent an improvement over prior art techniques, additional testingmethods are needed to properly and fully exploit the opportunitiesprovided by remote diagnostic systems as well as hospital or clinic sitediagnosis. The common approach to functional testing of the motorability of elderly persons is based on scoring the performance ofcomplex functional tests such as “Get Up and Go”, “Fregley Ataxia TestBattery” and others. The resulting score is used for estimating the riskof falling, mainly, for purposes of epidemiological studies. Each testconsists of a set of simple motor tasks. For clinical decision-making,physicians generally take into account the results of the separatetasks, instead of the resulting score of the whole test. It is knownthat the ability to perform a simple motion task is directly connectedwith concrete medical conditions of a subject/patient whereas theresulting score only provides a general impression. These tests veryoften require special equipment (e.g., static and dynamic force plateswith or without feedback, markers on specific body locations, and 6 to10 meters of walkway etc.). Moreover these tests require the presence ofan assistant to guide the test and insure the accuracy and safety of itsperformance. As a rule, such testing can only be realized in a clinicthat has the required equipment and a sufficiently skilled staff.Likewise, such testing is too expensive for everyday practice, usuallycannot be repeated as often as necessary and therefore cannot be used toperform thorough monitoring of elderly subject/patients with restrictedcapacities to visit clinics.

U.S. Pat. No. 5,980,429 (“the '429 patent”) describes a monitoringtechnique for training programs where effectiveness of training isassessed through a thorough comparison of quantitative and qualitativemeasured parameters with quantitative and qualitative benchmark data.Qualitative parameters relate to the accuracy of performing the tasksand quantitative parameters to a number of successive performances in acertain period of training. To obtain a sequence of qualitativebenchmark data, training tasks are arranged by level of difficulty ofperformance. The measured results of a given task are categorizedaccording to the completeness and accuracy of its performance. Thus asystem for objective assessment is realized. Benchmark data are definedfrom previous subject's performances or from data derived fromcorresponding reference groups. The “Sew Balance Master” test forassessment of motor and balance ability of a subject/patient describedin the '429 patent is a typical example of a well-designed clinicaltest. The training program is intended for persons with an intactcentral nervous system, i.e., can only be applied in specific injuries.Moreover, the assessment always relates to a person that does hishardest exercises on his own highest level. Hence the arrangement of themotor tasks by degree of difficulty may be adequate even if the accuracyof the assessment is restricted by dividing the results of measurementsover 3 to 5 categories.

However, an elderly subject performing tasks in accordance with suchtesting schemes, without any assistant, will mostly carry out the taskson a far lower level than his or her maximum abilities. So, the tasksshould be designed with a degree of difficulty but free from essentialmuscle tension and unstable poses that could lead to a fall. Moreover,nervous and physiological disorders, often present in elderly persons,necessitate individual tailoring of the difficulty level of the tests.Taking into account the fact that in elderly persons many essentialdisorders, associated with motor difficulties, evolve very gradually,the monitoring system should be able to detect small trend changes inmotor behavior of the subject/patient.

Thus, it can be seen that techniques leveraging the availability ofvideo image data, i.e., that build upon and improve the teachings of the'047 and '649 patents, would be an important advancement of the art.Furthermore, testing methodologies, including testing contents andprotocols should take advantage of these advances, thereby maintainingand improving the diagnostic reliability of current medical techniques.

SUMMARY OF THE INVENTION

The present invention is directed to improvements to the interactivevideo and audio subject/patient monitoring system disclosed in the '047and '649 patents by providing a video processing technique wherebymotion characteristics are readily discerned from video image data of asubject/patient. (The term “subject/patient” as used herein is to beinterpreted broadly to include elderly persons, persons actively beingtreated or monitored for specific medical ailments, as well as personswho need to have their general medical condition and gait and balancestatus monitored by practitioners for any reason, for example:astronauts in space stations etc. Additionally, persons who are beingmonitored for psychological condition, mood, truth telling and generalphysical condition are considered subject/patients. By way of example,but not limitation, interrogation techniques which rely upon physicalresponse to evince truthfulness or falsehood may utilize variations ofthe techniques disclosed herein along and in combination with otherphysical response measurements such as respiration, heart rate, etc.)Furthermore, the present invention sets forth a system of motor tasksand protocols for their execution that is particularly adapted for usein the interactive television and audio monitoring system as well asbeing useful at a hospital or clinic site where clinicians work directlywith subject/patients or any other remote monitoring scenario. Anexample of a series of diagnostic tests is disclosed wherein the testsare susceptible of qualitative, quantitative and/or image processingreview and analysis. The term “medical” herein is broadly inclusive ofphysical, psychological and behavior conditions by way of example.

The image processing techniques enable diagnosis associated withskeletal and muscular movement in a highly quantitative and recordablemanner. Thus, the video image of the patient performing each of thetasks in the protocol is captured by a video acquisition system. Thevideo image data is received in the form of a sequence of equally spaced(in the time domain) images. The acquired images are then compressedusing standard image compression techniques such as that defined byMJPEG compressed images in order to reduce the data content to allowstorage on a local disk or to allow transmission to a remote location.Unlike neuromuscular motor activity measured in standard gait andbalance laboratories which require a multitude of cameras and requirethat markers be placed on the patient, the present invention, withoutlimiting it, produces adequate results with the use of a single cameraand without the use of markers.

A pre-processing element follows the image acquisition. The purpose ofthe preprocessing element is to remove the background and produce asequence of silhouette images or outline images of the patient on aframe-by-frame or field-by-field basis by applying a sequence ofstandard image processing operations on the acquired images. The imageprocessing operations, well known in the art, include contrast control,brightness control, segmentation and edge detection. The pre-processingsequence of operations may be manually defined by an operator of thesystem or automatically discovered through the use of quality indicatorsand feedback to search for the best set of operations.

The pre-processing may be performed at the central location or at theremote location in a distributed system. The result of thepre-processing is a plurality of matrices (one per frame or field of theoriginal video image sequence) containing the silhouette or outlineimage. In the case where the pre-processing is performed at the patientlocation, the resultant pre-processed file is transferred to the centralfacility for continued post processing.

A post-processing element follows the pre-processing. The purpose of thepost-processing is to make measurements of various parameters of thesilhouette or outline of the patient on a frame-by-frame orfield-by-field basis. The aforementioned parameters or mathematicalcombinations of these parameters represent physiological indicesassociated with gait and balance as with other neuromuscular motoractivities. An example of a measured parameter in the space domain isthe maximum height that a patient's foot is raised from the floor. Anexample of a measured parameter in the time domain is the time it takesa patient to complete a cycle while walking.

The results of the measurements from the post-processing are stored forlong-term to monitoring and trending. The system provides for thedefinition of predefined normal value ranges for the results as well asadaptive individual normal value ranges based on the historical datafrom a particular patient An alarm notification is provided when a valuefalls outside the expected normal range.

A graphical “finger print” of the patients walking pattern is obtainedby summing the is individual matrices provided from the output of thepre-processing and storing the result in a resultant matrix. This issimilar to placing each outline from a single frame onto a transparencyand placing the transparencies one on top of the other. The resultingpicture provides a unique characteristic template of the patient thatmay be analyzed and compared to previously stored templates of thepatient. Changes from the normal historical pattern represent changes inthe neuromuscular motor activity of the patient that may be indicativeof physiological problems.

An integral part of this invention is the protocols used to test thepatient. Each protocol is an action or a plurality of actions that thepatient must perform. Some of the protocols such as walking in astraight line or walking in place produce direct physiological protocolsproduce the indirect physiological information such as the ability tocomplete a sequence of balance tasks each of which are subsequently moredifficult resulting in a numerical grade. The combined tests aredesigned to elicit all necessary physical and neurological informationrelating to a patient's ability to perform neuromuscular motor tasks.The tasks are particularly chosen to maximize safety and to minimize theprobability of the patient falling down or otherwise losing balance whenperforming the tasks. To this end, tasks are preferably ordered bydifficulty within certain tests. The level of difficulty associated withthe said task thereby offers an inherent qualitative measure. Thisqualitative information quantized by the degree of difficulty is storedtogether with other quantitative results. The use of degree ofdifficulty has particular relevance in rehabilitation.

These and other advantages and features of the subject invention willbecome apparent from the detailed description of the invention thatfollows.

BRIEF DESCRIPTION OF THE DRAWING

In the detailed description of presently preferred embodiments of thepresent invention which follows, reference will be made to the drawingscomprised of the following Figures, wherein like reference numeralsrefer to like elements in the various views and wherein:

FIG. 1 is a simplified, overall functional block diagram of the system

FIG. 2 is a schematic diagram illustrating one possible configuration ofthe home system

FIG. 3 is a schematic diagram illustrating one possible configuration ofthe central station.

FIG. 4 is a flowchart illustrating a method for video image processingin accordance with the present invention;

FIG. 5 is an exemplary raw video image prior to processing

FIG. 6 is an exemplary image after background subtraction and filtering

FIG. 7 is an exemplary binary image in accordance with the presentinvention;

FIG. 8 is an exemplary x-silhouette in accordance with the presentinvention;

FIGS. 9A and 9B are an exemplary motion portraits in accordance with thepresent invention; and

FIG. 10 is a drawing showing the various parameter measured from thesegmentation data.

FIG. 11 is an exemplary graphical representation of the outcome ofwalking in a straight line.

FIG. 12 is an exemplary graphical representation of the spectral densityof walking in a straight line.

FIG. 13 is an exemplary home layout for walking in a straight line.

FIG. 14 is an exemplary drawing showing the sequence of events in awalking cycle.

FIG. 15 is an exemplary report showing the values obtained from one testbased on walking in a straight line.

DETAILED DESCRIPTION OF THE INVENTION

A. General Description of System Hardware

The system of the present invention consists of two distinct entitiesFIG. 1, one is a subject/patient unit, located in the area where thesubject/patient performs the measurement, this unit is also typicallyreferred to as the home unit 11 since it is placed in the home of thesubject/patient in one of the preferred embodiments and a second entity,a central unit 12 located in the area where the medical practitioneradministrates the conduction of the measurements and analyzes theresults. The two entities are connected via a wideband communicationchannel 13. This configuration allows for the central unit to beseparated from the home unit. It also allows for a single central unitto communicate either serially or simultaneously with more than one homeunit. In both of these instances a public carrier provides thecommunication channel where the Internet is one of the possible means ofcommunications. The configuration also allows for local use such as in aclinic or hospital where the communication channel may be a local areanetwork. It further allows for very remote use such as the possible tocommunicate between a ground control and an orbiting space shuttle.

The system of the present invention uses or incorporates relativelyinexpensive home medical monitoring equipment that includes one or morecameras. When used as part of a home monitoring system it may includeadditional sensors and measuring devices for the particularphysiological/medical parameters to be monitored. The subject/patient'sremote location/home equipment is simple to use and modular to allow forthe accommodation of the monitoring device to the specific needs of eachsubject/patient. To reduce production costs and to avoid complexmaintenance problems, the remote home unit includes the absolutelyneeded components of the measuring device while most of thesophisticated elements are located in the central unit. The raw data,including video image data, is transmitted to the central station, whichincludes all of the needed sophistication to allow for the storage,transformation, display and interpretation of the data. The need forexpensive equipment in the remote location/home is thus avoided.

The central station includes a computer-based multi-channel dataanalysis and display unit that enables the interpretation, display, andstorage of the transmitted data. This central station is preferablyequipped with alarm mechanisms to alert the staff to any aberration fromthe expected. The central station further includes apparatus for thecommunication of data to all authorities involved in the wide spectrumof the subject/patient's needs, e.g., emergency care agencies, thesubject/patient's physicians, nursing services, social workers, etc.

The central station is preferably provided with the capability ofautomatically scanning predesignated subject/patient remote/home unitsat predetermined intervals to provide continuous supervision of specificparameters. In some instances, the central station may monitorcontinuously one or more parameters, e.g., ECG, blood pressure,respiration, etc. The embodiment disclosed enables one highly trainednurse or subject/patient-monitoring personnel located at the controlcenter to supervise and monitor as many as 50 subject/patients eitherseriatim or substantially simultaneously. Whereas a visiting nurse mayonly be able to visit 5 or 6 homes per day in person, a nurse at thecentral station may be able to visit 5 or 6 subject/patients per hour bymaking electronic “home visits”.

Any broadband communication system is suitable for the bi-directionalreal time contact with the subject/patient in the remote location/home.One such medium is cable television that provides an already existing,widespread and highly suitable system via cable modems for interactivevisual communication with most residential units in densely populatedurban areas. The ambulatory subject/patient monitoring systemintegrating the latest advances in biomedical technology with cabletelevision or any other available and suitable communication systemprovide safe and accurate general and medical supervision for thegeriatric/homebound population in their own, natural environment.

It will be appreciated that as advances in telecommunications develop,other techniques for transmission of video signals between a centralstation and the home may be desirable and economically feasible. Forexample, satellite and radio transmission of the video signal and/ormonitored medical data, or transmission via modem through the telephonelines, may also prove satisfactory. In due time the system will possibleusing the internet or similar computer networks as it's maincommunication system both for the data transmission to and from theremote location/home as well as the use of the database by otherauthorities such as physicians insurers, government agencies, etc.

A typical embodiment of the home system is shown in FIG. 2. A singlecamera 22 is used to take a motion picture video of the subject/patient21. The camera has a wide angle and provides for remote control from thecentral station for pan, tilt, zoom as well as other controls such asbrightness and contrast. Typically the camera will provide 30 frames persecond and transmit composites or supervideo signal in NTSC standard tothe video acquisition 23. The video acquisition will acquire the analogvideo signal and convert it to a digital Y Cr and Cb values. The Y Crand Cb values are then passed through a video compression component thatcompresses the video. The compressed video may be locally stored in adisk 24 for later transmission, this is necessary in the case that thedesired communication bandwidth is not appropriate to transfer thecompressed video in realtime or directly transferred as part of anintegrated video-conferencing system 25. In addition the integratedvideo-conferencing system 25 provides for interactive audio-visualinteractions with the central station so that the subject/patient maysee and speak with the medical practitioner on the home TV set 26 andthe medical practitioner may see the subject/patient on the centermonitor. The interactive communication is an important aspect of thesystem in that it allows for the medical practitioner to instruct thesubject/patient to perform the testing and to monitor thesubject/patient while the tests are being performed. It should be notedthat the video quality required for monitoring the subject/patient maybe less than the video quality required for the automated neuromuscularmotor analysis of the patient. Video conferencing may be performed usingeither standard H.323 compression or using more proprietary compressiontechniques such as wavelet compression. The audio signal may bedigitized and received and transmitted in either a compressed ornon-compressed format. Should the video be stored locally as a file ondisk 24, it would transmitted to the central station as a file usingcommon communication transfer protocols such as TCP/IP to insureintegrity. The acquisition, storage and videoconferencing may beimplemented using a standard PC, in this case the various elements areimplemented as PCBs which reside on the bus of the PC. The controlprogram and the video conferencing application run under the operatingsystem of the PC. An alternative implementation would be to use anembedded system with a microprocessor and DSP to perform theacquisition, compression and video-conferencing functions.Communications is provided by an interface to a standard communicationmodem. This may be a cable modem, xDSL, ISDN or other broadbandcommunication modem.

A typical embodiment of the nurse station is shown in FIG. 3. Imagesarrive into the central station from the communication system 31 and arestored on a local disk 32. This element also provides forvideo-conferencing with the home system. The online images are seen in awindow on the local display 33. Images stored on the local disk 32 arethen preprocessed by a preprocessing application 34. The preprocessingapplication removes background information, obtains an outline orsilhouette of the subject/patient on a frame by frame or field by fieldbases and performs x and y segmentation of the images. The results ofthe preprocessing are stored in an x and y segmentation file of theimage 35. The x and y segmentation files may be used to obtain afingerprint of the image figure xx or may be used for post processing36. Post processing transforms the results of the x and y segmentationto meaningful quantitative and qualitative information as a function ofthe specific test which was performed. Post processing are the set ofalgorithms used to extract the desired data for the x and y segmentationand to perform the necessary manipulation of this data based on thefeatures which are desired to extract from the data. The post processeddata is stored in a data base 37 together with other patientinformation. This data becomes part of the historical record of thepatient and may be used to compare present data with past data, triggeralarms as seen on a display window 38 when any parameter resides outsidethe expected range and be used by reporting applications 39. Owing tothe fact that the data resides in a database the data may be queried byother application programs which may run either on the local system oron a remote system which communicates with the data base. An example ofthe latter is a system running at a doctors office which may monitor theresults of a particular patient.

B. Hospital or Clinic Analysis

While an important aspect of the described techniques is remote sitemonitoring, the protocols described hereinafter have significantlybroader application and utility. That is, the described image monitoringmay be conducted at any site including in hospital or at a clinic. Inevery circumstance, the images and other data are recorded, analyzed,stored or retained and compared with historic information or standardinformation. The practice of the described image processing andprotocols at a hospital site will, for example, be a useful diagnostictool for the medical practitioner. Thus, the described invention, thoughdetailed in the context of remote monitoring, is equally applicable foron-site monitoring of subject/patient condition, both ill and well, andis an important diagnostic tool for on-site use.

The prevent invention utilizes a multifaceted approach to medicaldiagnosis relying upon the interactive technology heretofore describedand the technology described in various co-pending applications. Animportant feature of such multifaceted diagnosis and a principal featureof the present invention, is video image processing of a patient toanalyze gait, balance, skeletal condition, muscle condition andcoordination and other physiological features and conditions. Briefly,video images of the outline of the body or a part of the body arerecorded and analyzed either by a trained physician or nurse or bymachine analysis in an effort to detect (a) a base line of performanceor condition (2) variation from norms (3) changes over time (4) changesunder stress, and (5) changes in emergency conditions. The imagingtechniques may be utilized by themselves or in combination with other,diagnostic techniques, including traditional techniques, as well as testtechniques described herein. The images are, in the system described,obtained by using video camera input signals obtained from thesubject/patient location. However, the general techniques of imageanalysis are not restricted to such a monitoring system. Thus, they maybe used, for example on site at a hospital.

C. Video Image Pre-Processing

Referring now to FIG. 4, there is illustrated, a system for performingvideo processing of images from a single video camera without markers onthe subject in accordance with the present invention. In particular,FIG. 4 illustrates a preferred grouping of algorithms or subsystems41-47. In one embodiment of the present invention, the systemillustrated in FIG. 4 is implemented using PC or similar processingdevice executing software instructions stored in memory. Those havingordinary skill in the art will recognize that various implementations ofthe functionality described below, other than those illustrated in FIG.4, are possible as a matter of design choice. Furthermore,implementations need not be restricted to a software implementations;for example, dedicated hardware devices may be used to implement certainportions of the functionality described below. Finally, the processingillustrated in FIG. 4 and described below is preferably carried outautomatically upon reception of video image data. Alternatively, thevideo image data may be stored indefinitely, and the processing of FIG.4 carried out only upon command.

Video image data from a single camera is received (via cable 31, forexample) by a preprocessing subsystem 40. Preferably, the video imagedata is color video data in a digitized and compressed format having acompression ratio of about 10. In practice, it is preferred that thecamera 22 providing the video image data be positioned and fixed (so asto provide a static viewing area) at a location approximately 3 metersaway from a gait path or other performance area to be used by thesubject/patient. The pre-processing subsystem 40 performs conditioningsteps necessary to place the video image data in a form suitable forcontinued processing. For example, the pre-processing may include, butis not limited to, noise suppression (smoothing) filters, and colorpreprocessing (brightness/contrast adjustment, histogram stretch,decreasing the number of used colors, i.e., bit-per-pixel). As onealternative, interlaced fields may be used, rather than frames. Thevideo image data output 47 by the pre-processing subsystem 40 isessentially a series of digitized images of the subject/patient,preferably performing one or more tasks such as walking, etc.

Each frame output by the pre-processing subsystem 40 is provided to aquality subsystem 45 and a segmentation subsystem 47. The qualitysubsystem checks the quality of each image and modifies the variousthresholds used in the processing if the quality is not acceptable.

Thus, prior to filming the subject/patient, an image of just thebackground alone, i.e., the area where the subject/patient is to befilmed, can be obtained by the system. This background-only imageprovides current background parameters. The calibration subsystem 46then reads the environment parameters from a previous session forcomparison with the current background parameters. Environmentparameters include the color distribution model (illumination model) andcamera parameters such as the lines or pixals, contrast sensitivity,etc. for a previous session. The environment parameters may also includea subject/patient's figure templates, i.e., data generally describingthe subject/patient's dimensions and appearance. In the case where theprevious and current environment parameters are very similar (as wouldbe the case, for example, where the subject/patient always performs thetesting at the same location), the successful video processing settingsof the previous session are provided to the segmentation subsystem 47for application to the image currently being processed. In the case of anew subject/patient or of essentially different previous and currentenvironment parameters or inconsistent results of the test processingwith the setting of the previous session, the processing parameters arechosen interactively applying varying combinations of processing toolsto small portions of the images.

The parameters selected by the calibration subsystem 46 and the videoimage data from the pre-processing subsystem 41-45 are provided to thesegmentation subsystem 47. In the context of the present invention,segmentation refers to the process of creating binary (i.e., all pixelsare either black or white) or gray-scale (i.e., all pixels assume avalue somewhere between the extremes of black and white) images of thesubject/patient. To this end, a variety of techniques may be employed.One technique, edge detection processing, can be performed to discernthe edge's of the subject/patient's image. For example, edge detectionfilters combined with thresholding (in which all values above a certainthreshold are deemed black or white, and all values below the thresholdare deemed the opposite) may be used. Alternatively, edge detectionfilters in combination with edge tracing as taught, for example, by S.M. Smith in “Reviews of Optic Flow, Motion Segmentation, Edge findingand Corner Finding”. Techn. Report TR97SMS1, Oxford Centre forFunctional Magnetic Resonance Imaging of the Brain (FMRIB) Department ofClinical Neurology, Oxford University, Oxford, UK, 1997, the teaching ofwhich are incorporated herein by this reference.

As noted above, background or environment parameters provided by thesegmentation subsystem 47 may be used to subtract the background colors,leaving substantially little more than the subject/patient's image.Thus, the background parameters can be pixel color values, stored in atable, corresponding to various regions (preferably non-contiguous)within a given image. All pixels values in the image near or identicalto the stored pixel values are then subtracted to remove the backgroundcontent. In yet another alternative, the pixels of all images are firstseparated into a small number of groups according to features of imagesdistinguishable by their color (using statistical criteria as taught,for example, by D. Comaniciu and P. Meer in “Robust Analysis of FeatureSpaces: Color Image Segmentation”, Techn. Report, Rutgers University,Piscataway N.J., 1997, the teachings of which are incorporated herein bythis reference). Subsequently, the images are binarized using one of theabove mentioned methods, e.g., edge detection and thresholding. Finally,combinations of the above techniques may be used. FIG. 8 illustrates anexample of a binary image resulting from a color image in which thebackground content has been removed in accordance with the teachingsabove, and which has been passed through thresholding.

The binary or gray-scale images resulting from the binary processing 43are provided to a boundary tracing subsystem 44 where the binary orgray-scale images are processed to provide only an outline or silhouetteof the subject/patient in each image. In one embodiment, a so-calledx-silhouette is used for this purpose. An x-silhouette comprises allpoints of a binary or gray-scale image lying at the leftmost andrightmost points lying on a horizontal line through any section of thesubject/patient's figure.

Another alternative method for boundary tracing is to take a givenimage, with or without background subtraction, and shrink the image by aknown factor, i.e., by a factor of 4 to 5 thus producing an image whichis ¼ or ⅕ the size of the original image and resealed back up to theoriginal size using the same factor. The result is a reduce resolutionimage. By subtracting the reduced resolution image from the originalimage, a good approximation of the subject/patient's boundary isprovided. In one embodiment of the present invention, this technique isused periodically, i.e., every 5^(th), 10^(th), etc. image. The boundarythus generated is then used as an approximation to the subject/patient'sfigure boundary. All image processing and boundary tracing proceduresare then performed in a relatively small neighborhood of thisapproximate boundary. Additionally, the approximations may be used as abasis, along with a complete silhouette, for interpolating pointsotherwise missing from incomplete silhouettes.

The following is an example of the use of the above methods. A pictureof the subject is shown in FIG. 5. The goal of the image processing isto remove the background and obtain a silhouette of the image. A secondimage exists in the system, taken without the subject in the picture.This image is referred to as the background image. The background issubtracted from the image of FIG. 5 on a pixel by pixel basis. Thismeans essentially that if each pixel in a given frame is designated asan element of a matrix Pixel[FRAME,I,J] where the pixel located in theI^(th) row and the J^(th) column of the frame FRAME then the subtractionoutput is obtained by performing the subtraction ofPixel[FRAME,I,J]−Pixel[REFERENCE,I,J]. The result of the subtraction isthen filtered using a low pass averaging 7×7 pixel filter. Thisoperation produces the image seen in FIG. 6.

The next step is to produce a binary image by setting a threshold suchthat all pixels values above the threshold are set to black and allvalues below the threshold are set to white, see FIG. 7. The next stepis to perform edge detection on the binary image. The result of the edgedetection is shown in FIG. 8. The output of edge detection is used toobtain couplets of data points in the x direction. The first member ofthe couplet is the start of the edge detected image in a given row andthe second member of the couplet is the end of the edge detected imagefor the same row.

The matrix of couplets of the rows is referred to as the x segmentationmatrix. A similar process is performed on each of the columns resultingin a y segmentation matrix. Further still, an x-segementation matrix,i.e. the matrix W indexed by a row index, j, and a frame index, k, isdefined as:

W[j][k]=X _(r) [j][k]−X _(l) [j][k] for j=1, 2, . . . , N _(rows) andk=1, . . . , N _(frames)  (Eq. 1)

where X_(l)[j][k] and X_(r)[j][k] are the x-coordinates of the most leftand right points respectively in the intersection of thesubject/patient's figure on the i-th frame with the j-th row, N_(rows)is the number of rows in a fixed rectangle containing the union of thesubject/patient's figures in all frames, and N_(frames) is the number offrames. Based on the x-segmentation matrix, left and right x-velocitiesand x-acceleration matrices, i.e. the matrices defined as the first andthe second differences of the matrices X_(l)[j][k] and X_(r)[j][k] withrespect to the k-th frame may also be defined.

D. Post Processing

One example of the use of the silhouettes, regardless of how they areproduced, the silhouettes generated in this manner are combined as apixel-wise conjunction or superposition of all silhouettes to provide amotion portrait. Stated another way, let Img[1], Img[2], . . . Img[N] besequence of silhouettes generated as described above. The union of allImg[j] for j=1 to N is a motion portrait. An exemplary motion portrait,comprising a union of full silhouettes, is illustrated in FIG. 9. Asshown, each of the black pixels corresponds to an object in motion. Itis understood that motion portraits may be constructed fromx-silhouettes, y-silhouettes or full silhouettes and, in one embodimentof the invention, motion portraits from each type of silhouette areprovided.

Depending on the condition of the subject/patient performing the tests,the motion portraits thus provided may be used to detect anomalies orother artifacts in the subject/patient's performance. For example, whena normal healthy subject/patient performs a gait test, the motionportrait will typically exhibit a smooth appearance in that themotion-based pixels will be evenly distributed throughout the motionportrait. On the other hand, for the same subject/patient walking witheven a slight limp, the motion portrait will often be characterized byclusters of motion-based pixels with noticeable frequencies. Althoughsuch visual analysis of motion portraits can be used by skilledpractitioners to detect various medical conditions, the presentinvention also provides for more analytical analysis of motionportraits. FIG. 9a shows a motion “finger print” of a normal walk, whichcan be easily distinguished from the motion finger print of an abnormalwalk FIG. 9b.

In particular, motion portraits can be processed by a motioncharacteristics calculation in the post processing stage. Generally,motion characteristics include any qualitative measurements that may becalculated based on the motion portraits. For example, discrete motioncharacteristics such as step length, the duration of carrying out ofstages of motion tests, characteristic frequencies of the motion(especially, of the gait tests) can be calculated. Head motioncharacteristics (i.e., the slope, the top-point trajectory) or, moregenerally, trajectories of characteristic points of thesubject/patient's figure (i.e., the center of gravity, knees, heelsetc.) may also be directly calculated from the motion portrait dataTypical data extracted from the x segmentation matrices, FIG. 10, arethe coordinate values of the subject/patient summit, the extreme leftand right points of the outline at the hands level, and the spectrum ofthe subject/patient's instant velocity on a frame by frame or field byfield bases. Typical values from the y segmentation include timing(initial contact, push off and middle swing instances for both sides,the step width, and the sagittal projection of sole-floor angle at someinstances for both sides. Other information include the silhouette area,the coordinates of the arbitrary center of mass of the silhouette. Sinceall of the silhouette outlines are defined for each frame or field andbecause each frame or field represents an inherent clock timing a graphcan be made showing the various parameters and the subsequent changes inthese parameters over time. The oscillations of the parameters obtainedfrom the x segmentation have extremes that in normal walking strictlycorrespond to temporal parameters revealed from the foot-floor contactevents.

The graphs in FIG. 11 illustrate the above process. This graph shows thesagittal projection of the head summit motion vertical component. The Xaxis of the graph is the time reference in frames (i.e. {fraction(1/30)} second per frame). The Y axis is a distance in pixels. Verticalmotion is projected with a resolution of 1 pixel or 0.5 cm. The motionin the frontal plane is projected with a resolution of 1.5 cm. Markersin the graph show the various timing events on the curves. An asteriskmarks the initial contact (IC), a square marks the initial push off (PO)and a circle marks the middle single support (MSS). RF is used toindicate the right step and LF is used to indicate the left step. Theterminology of these events are common in the gait and balancelaboratory. The left graph is a pattern of normal walking of a youngman. The right graph in FIG. 11 corresponds to walking of the same manbut with his right knee mechanically restricted. Frontal motion of thesummit causes asymmetry in the height of the peaks. Nearer to the cameraside produces higher peaks. This difference expressed in centimeters israther close to the width of the walking base. The difference betweenthe minimums is much smaller because the lowest points of the summit isvery close to the central (sagittal plane) The knee stiffness producesasymmetry in the minimum deepness. Finally, fourier transforms of all ofthe above motion characteristics, including discrete sine- andcosine-transforms, power spectrum, etc. transforms may be calculated,see FIG. 12.

These motion characteristics, while not exhaustive of all motioncharacteristics that may be calculated based on motion portraits, may beused by a physician or other skilled practitioner to determine theexistence of trends demonstrating improvement, deterioration or nochange in a subject/patient's condition.

Alternatively, a comparison subsystem is provided. In particular,previous data including, but not limited to, motion portraits and/ormotion characteristics data from one or more previous sessions with agiven subject/patient, is stored. The previous data may also comprisenormal data for the subject/patient, i.e., data corresponding to a timewhen the subject/patient was generally in good health. By comparingcurrent motion characteristics and/or motion portraits with previous ornormal motion characteristics/motion portraits, practitioners can detectdifference between the two and, based on their experience and expertise,draw diagnostic conclusions.

As another alternative, motion characteristics data may be comparedagainst predetermined thresholds (for example, determined based on anaveraging of values for a given characteristic in a large sample ofsimilarly situated subject/patients) to assess the subject/patient'scondition. Health care practitioners and those generally having skill inthe art will recognize that a variety of comparison and/or otheranalysis methods may be used in assessing a subject/patient's condition.

E. System of Motor Tasks and Protocol

The use of video image processing, as described, may be combined with atask oriented examination and diagnostic protocol. An example of such aprotocol is discussed hereinafter. Briefly, a series of patient tests orexercises are specified for performance by the subject. Physiologicalmeasurement, qualitative analysis of the responses, quantitativerecording of vital signs, and video imaging are all recorded with acomposite result being indicative of the health of the subject. Thesubject will be diagnosed with respect to illness or infirmity and withhealthy subjects, a normal baseline will be established. Thus thefollowing protocol is an example which may be varied or alternativeprotocols may be adopted.

In order to properly exploit the power of such monitoring, a system ofmotor tasks and a protocol for carrying them out should be defined suchthat the different environment in which they are performed, is takeninto account. In particular, motion, gait and balance testing shouldtake into account the following conditions: (a) as a rule, the nervoussystem of the subject/patient is disordered because of age and/ordisease; (b) absolute safety, i.e. a zero probability of falling duringtesting is required because of the absence of assistance that couldprovide a guarantee against an accidental fall; (c) only remote oral andvisual instructions, warnings and explanations are available for fallprevention; (d) no expensive gait analysis techniques can be effectivelyused; (e) testing procedures should performed quickly and easily; (f)only one Pan-Tilt-Zoom type video camera is used; and (g) the monitoringtechnique and comprehensive examination must reveal any kind of changein the medical condition of the subject/patient relating to hisbalancing ability.

Although the last requirement seems to be incompatible with the previousconditions, a compromise can be found: (a) for nervous disorders, motortasks can be ranked within one test, checking a specific kind ofactivity and not trying to arrange the tests by difficulty ofimplementation; (b) a protocol of examination, including conditions ofaudio visual recording, can be strictly standardized for a givensubject/patient; (c) monitoring can be organized to maketime-comparisons of the measurements and observations; (d) safety can beprovided by extracting from the complete functional tests (from “Get Upand Go”, for example) only the necessary tasks, and combining them sothat they may be done near a wall, a chair back, corner or other similarsupport.

1. Instrumentation

An audio-visual recording system and image processing, as describedabove relative to FIGS. 1-4, is the preferred means for obtainingkinematic information resulting from performance of various tasksselected for a given subject/patient. As noted above, only one videocamera is required for this purpose; it's orientation, zoom, shutter,gain and white balance can be controlled remotely from the centralstation. Optionally, other instruments may also be used, including anECG instrument for indirect measurement of exertion or equipment tomonitor quantitatively, e.g., blood pressure non-invasively before andafter an exercise. Further still, additional video cameras may be usedto monitor activities of the subject/patient or for comparative analysesand data acquisition from distinct orientations.

2. Tests and Tasks

In a preferred embodiment there are eleven (11) tests or groups oftasks. The tests are designed to enable checking all mechanical andnervous mechanisms of stability, and an exemplary set are listed inAppendix A with a more detailed explanation of each test set forth inAppendix B.

The procedure of the examination is adapted to conditions of monitoringin the home without any physical assistance though it may be used in ahospital or personally monitored environment. Safety is ensured throughthe use of verbal instructions and warnings. To further ensure safety,many tasks have been modified or even discarded, e.g., stepping over anobstacle, transferring, etc. Other tasks standard tasks have beenmodified to provide acceptable conditions for audio-visual recording inrestricted room sizes, e.g., free level walking, changing speed, abruptstop etc. All tasks including dynamic perturbations of balancing instanding are self-initiated without any use of external forces. As shownin Appendix A, each task is grouped under a corresponding test accordingto the test identification number. Furthermore, within each group ofrelated tasks, the tasks are generally ranked in order of increasingdifficulty.

3. Protocol of Examination

For any given subject/patient, about 8-10 tasks in total are selectedfrom among the various tests as a basic check for regular monitoring.The basic check is performed to provide an entire body of physical andneurological information relating to balancing ability of the givensubject/patient. Given the relatively small number of tasks to becompleted, it is anticipated that the basic check or protocol can beperformed in 5 to 7 minutes.

Ordering the tasks by their level of difficulty saves on the amount oftasks that have to be carried out because, for each test, it isgenerally enough to carry out only one or two tasks given the historicaldata for the subject/patient. That is, once a subject/patient hasdemonstrated an ability or inability to a test at a given level ofdifficulty, later examinations can be tailored to include only thosetasks at the next higher or lower difficulties levels. Also, such aprocedure is the most informative in that the maximum amount of thefeatures are revealed. The practitioner immediately obtains the keyvalue: the difficulty level that, together with relevant informationfrom the conversation with the subject/patient, serves as a basis forcontinuing, interrupting or changing the current examination program. Ofcourse, the tasks may be flexibly altered during an examination asdeemed necessary by the practitioner. For example, where undesiredchanges are detected or ambiguous results obtained, the practitioner caninvestigate more thoroughly by asking the subject/patient to performother tasks within the same test. In this manner, a definition may bearrived at according to either the predefined basic test scheme or acurrent decision of the practitioner.

As a result of task implementation, three kinds of data are provided:quantitative, qualitative and images. Quantitative data, such astemporal and spatial parameters of a gait cycle (i.e., the motioncharacteristics described above), resulting from analysis of image dataare instrumental, being obviously objective assessments of asubject/patient's state. Appendix C lists quantitative variables thatmay be measured, the types of units (if any) applicable to eachvariable, and a data type used to express the value of each variable.

Qualitative data comes from observation (evoked balance strategies,anticipation reactions etc.) and special efforts are required for makingthis criteria fully objective. Appendix D first sets forth a list ofGraded Results expressive of various qualitative variables. The GradedScales list, also set forth in Appendix D, shows the various ranges orscales of measurements relative to each qualitative variable. In thismanner, observations by practitioner may be translated into relativelyobjective data that may be tracked in a manner similar to thequantitative data.

Additionally, because all tasks within one test are arranged by theirdegree of difficulty, the order of the tasks becomes a benchmark valuebecause of its objective nature. Stated another way, the difficultylevel of each task inherently serves as a benchmark. In order to providea fine scale for grading, a set of tasks, each with a minor increase indifficulty, is defined for benchmark testing. If the gap in such a“scale” becomes too large then a new task can be inserted. For example,a non-standard task “Standing on foot and opposite toe” covers the spacebetween the “Two feet together” and the “One leg stance” tasks. Some ofthe tasks can be adjusted to a finer gradation with the help of certainmechanical parameters. For example, putting a weight on asubject/patient's wrist during the task “Dynamic Center of Gravity (COG)Shift” varies the difficulty level and could play the role of a finecalibration tool. Navigation of the subject/patient over such a set ofbenchmark data directly points to improvement or deterioration ofhis/her condition.

In summary, standard functional tests of gait and balance abilities inelderly subject/patients inadequately meet the requirements of thehealth monitoring service of ambulatory (in home) subject/patients aswell as hospital site subject/patients. Therefore, the present inventionproposes a technique, comprised of a specific approach to obtaining,analyzing and representing results; a set of tests mostly containing asubset of motor tasks; and a protocol of carrying out the examination.Results of the examination are divided into two parts: first, a level ofdifficulty of performance of a current motor task for a givensubject/patient that immediately and objectively gives an initialapproximation to a measurement of the motor ability of thesubject/patient and, second, all other quantitative, graded qualitativeresults of measurements and image processing. Additionally, desiredobjective and fine monitoring are achieved by comparing session resultswith each other.

The set of tests is complete enough to check all essential aspects ofthe ability to maintain balance in rest, through steady locomotion andmaneuvers. The tests are groups of motor tasks arranged by their levelof difficulty. This arrangement may be quite individual for a givensubject/patient with a certain combination of nervous and physiologicaldisorders. The tasks are safe and informative. The protocol ofexamination provides validity through the comparison of session results.This is attained through the standardization (for each subject/patient)of the procedures of implementation and conditions of audio-visualrecording. The protocol is adapted to home conditions and the absence ofan assistant: for safety, all maneuvers are preferably carried out nearthe wall, corner or other support where necessary. Because a health carepractitioner at the central station deals only with objective factsconcerning the performance of the tasks, they are not burdened with theinterpretation of results. A more skilled practitioner can then performoff-line analysis of the data obtained during the examination. Oneexample of a task and their assessment correlating qualitative,quantitative, and video image results follows:

4. Example

One given test is produced by having the subject walk in a walk in astraight line perpendicular to the camera FIG. 13. The subject walksthis path for a prescribed number of times. Each time the opposite sideof the subject is close to the camera. The walk is filmed andtransferred to the central station. The video images for each path areappended one to the other to obtain a longer time (i.e. more walkingcycles) for statistical analysis. The image then goes through thepreprocessing cycle to produce x and y segmentation matrices.Information pertaining to the gait and balance cycle for mid singlesupport, push off, initial contact, see FIG. 14, are extracted for eachcycle. The information is used to produce a graph such as shown in FIG.11. The graph is then analyzed to build a table of data as shown in FIG.15. The data in FIG. 15 along with the segmentation matrices are storedin the database. Abnormal data causes an alarm message to appear on thescreen.

While the foregoing detailed description sets forth preferably preferredembodiments of the invention, it will be understood that many variationsmay be made to the embodiments disclosed herein without departing fromthe true spirit and scope of the invention. This true spirit and scopeof the present invention is defined by the appended claims, to beinterpreted in light of the foregoing specifications.

What is claimed is:
 1. A method of processing video image data, themethod comprising the steps of: generating, based on the video imagedata, a plurality of silhouettes of a figure represented in the videoimage data; forming a plurality of matrices, each matrix representing asilhouette in a frame of the video image data; establishing a motionportrait from the plurality of matrices and based on the plurality ofsilhouettes; and calculating motion characteristics from the pluralityof matrices and based on the plurality of silhouettes, wherein themotion characteristics are used to medically diagnose the figurerepresented in the video image data.
 2. A method of measuringphysiological characteristics of an individual with respect to movementof said individual comprising, in combination, the steps of: videorecording the individual performing a predefined routine of physicaltasks; processing, without human intervention, the video image recordedto define a silhouette pattern of the individual movement; comparing thesilhouette pattern with a standard; determining the deviation of thesilhouette pattern from the standard and determining whether at leastone physiological characteristic is outside an expected normal range. 3.The method of claim 2 wherein the standard is a normalizedrepresentative sample for the predefined routine.
 4. The method of claim2 wherein the standard is an historic recording of the individual. 5.The method of claims 3 or 4 further including a sensor to detect adeviation from the standard.
 6. The method of claim 5 wherein thedeviation exceeds a limit and a sensor is provided to detect theexceeded limit.
 7. The method of claim 6 wherein the deviation isannounced.
 8. The method of claim 2 wherein the predefined routinecomprises walking from a side profile.
 9. The method of claim 2 whereinthe predefined routine comprises conduct of an arm motion protocol. 10.The method of claim 2 wherein the predefined routine comprises conductof a head motion protocol.
 11. The method of claim 2 wherein thepredefined routine comprises a leg motion protocol.
 12. The method ofclaim 2 wherein the predefined routine is recorded from the backside ofthe individual.
 13. The method of claim 2 wherein the video image isrecorded and stored.
 14. A method for performing medical diagnosis basedon physical motion of an individual conducted pursuant to a pre-definedprotocol, comprising, in combination, the steps of: positioning theindividual in a field; causing the individual to move in accord with aninstruction; video recording the individual movement from a fixedposition; processing, without human intervention, the video image of theindividual to highlight the silhouette of the individual; and inresponse to the step of analyzing, determining whether the individualmovement is associated with an expected normal range. analyzing themodification of the video image by comparing the modification to astandard and in response to the step of analyzing, determining whetherthe individual movement is associated with an expected normal range. 15.The method of claim 2 or 14 including the step of performing a pluralityof recordings of the individual, each recording constituting distinctpattern or routine.
 16. The method of claim 15 wherein the patterns orroutines are of varied difficulty.
 17. The method of claim 15 whereinthe patterns or routines are of increasing difficulty.
 18. The method ofclaim 15 wherein the routine or pattern is varied quantitatively. 19.The method of claim 15 wherein the routine or pattern is variedqualitatively.
 20. The method of claim 2 wherein the tasks are groupedas a collection of at least two sets of tests and wherein at least onetask from at least two sets is conducted with an individual during asingle recording session.
 21. The method of claim 2 or 14 wherein atleast one qualitative measurement is conducted during a single videorecording session.
 22. The method of claim 2 including the step ofrecording at least one qualitative measurement for each task.
 23. Themethod of claim 2 or 14 including the step of recording at least onequalitative measurement.
 24. The method of claim 1, 3 or 14 using asingle video image source.
 25. The method of claim 3, further comprisingthe step of: ordering the plurality of separate tasks by associatedlevels of difficulty, wherein the step of instructing the entity isbased upon the step of ordering.
 26. The method of claim 1, furthercomprising the steps of: saving the plurality of matrices as a datastructure; and retrieving the data structure to obtain the plurality ofmatrices.
 27. The method of claim 1, further comprising: summing theplurality of matrices to form a graphical fingerprint, the graphicalfingerprint providing a unique characteristic template of a patient, thepatient corresponding to the figure.